Soil pH can be used as a general guide for determining nutrient availability and therefore
species that may grow on a given site. Within the framework of the Swiss National Forest
Inventory, more than 1'000 soil profile samples have been described across Switzerland and
samples have been analyzed regarding acidity.
The main objective of this study was to generate a top soil acidity map for forested areas in
Switzerland applying two regression model approaches: the ordinary least squares
regression (OLS) and the geographically weighted regression (GWR). Environmental factors
of climate, topography and vegetation were used as predictors to build quantitative
relationships. Besides these parameters, the OLS regression contained additionally nominal
variables which describe mainly geomorphological and pedological entities. Because the
GWR approach is able to represent spatial regimes, these nominal variables can be
neglected in the GWR model.
The strength of the predictive relationships were moderate for both regression types, with
adjusted R2 values of about 0.44 to 0.47. Considering that topsoil pH values are highly
variable, the model performance is satisfying on a nationwide scale.